How to Handle Rogue AI in the Enterprise while balancing security, compliance, and innovation in workplace adoption.
Artificial Intelligence (AI) is everywhere today, even when what’s described is not true AI. I’ve seen television commercials boasting toothbrushes using AI tech, for example. But the truth is that AI has become more than a scary apocalyptic fantasy, entering the mainstream lexicon as a useful tool to generate outputs. The fast proliferation of generative AI tools like ChatGPT has upended the marketplace understanding of what AI is and can do, and employees at businesses are increasingly leveraging AI tools to be more productive at work.
On its surface, this increased use of AI tools in the workplace is not bad. It is, however, something to keep an eye on, especially when the AI adoption is using unauthorized tooling, which could lead to security and compliance risks for your organization. The problem is that it’s impossible to control employees, locking everything down. Employees will always find a way around obstacles. It’s difficult to capture every detail of how technology is used, especially within a large enterprise. Plus, the AI applications are evolving and refining their abilities at a lightning pace, making it hard to keep the guardrails updated for each twist and turn.
Furthermore, to encourage innovation within your organization and gain an edge on competition, avenues like AI solutions must exist to adopt new ways to conduct business. This leaves IT leaders in a tough spot when trying to handle rogue AI in the enterprise effectively while ensuring enterprise AI security and proper AI risk management.
The Challenge of Rogue AI
You might be asking, what could be done to stop the deluge of rogue AI? Should I lock it all down? Should I throw my hands up?
When employees leverage tools through unofficial channels, it creates cybersecurity risks for the organization—and IT leaders need to step in and enforce proper use. Instead of banning unauthorized AI tools outright, IT leaders could take another approach: focus on educating the organization on responsible AI use. This will enable the secure, sanctioned use of tech tools more broadly, fostering innovation safely while maintaining enterprise AI security.
One use case comes from my own company. We created an internal chatbot for our employees to ask questions about organizational policies, decipher customer requests, identify AWS documentation, and submit Jira tickets. It also offers guidance on debugging. In essence, we used AI to create something that, in turn, would be useful to our employees in driving better AI usage more broadly. This approach helps handle rogue AI in the enterprise by integrating practical oversight with employee adoption.
Three Steps to Enable Strong LLM Policy
1. Educate on the Basics
Create an AI education program to demonstrate the foundational elements and different types of AI, including the pros and cons of each type of AI. Keep it simple, to make sure everyone understands. Knowing the risks and shortcomings of each tool is helpful to share with employees, as they can approach the named applications with a degree of caution. For example, they shouldn’t share your company’s proprietary information with ChatGPT, since it becomes a part of ChatGPT’s learning repository. This, in turn, would give your competitors access to that same data. Tangible examples will go a long way in making the educational content digestible and memorable. Many organizations don’t have the talent development resources to create an AI curriculum, and that’s okay! There are plenty of courses already created that you can leverage. Don’t reinvent the wheel.
2. Give Clear Guidance on the Risks
Employees don’t need to know the full spectrum of your compliance framework requirements to grasp the importance of good posture. Keep things at a high level, but be clear on the expectations and “the why” behind each policy rule. For example, if you are in a highly regulated industry, explain why using specific AI tools that, without permission, could put your organization at risk for significant regulatory fines, which could cost the company jobs if the bottom line is impacted unexpectedly.
Another risk to using generative AI is the line between what becomes the legal property of companies like OpenAI and yours. For example, if an employee uses content from ChatGPT for a new corporate slogan verbatim rather than making alterations, it belongs to the AI company rather than your own. Having your corporate legal counsel talk to employees about the legal implications could be a smart idea. This is also why we build on Amazon Bedrock at Mission. You know your data is safe. This step is critical for AI risk management and helps handle rogue AI in the enterprise proactively.
3. Create Guidelines to Encourage Innovation
This is where the rubber meets the road. Craft a set of rules with multiple departments and executive stakeholders in conversation to align on new policies. This approach will not only keep your sensitive data in check, but it will also encourage an environment of innovation within your organization. Provide alternatives to AI products if the AI an employee wants to use isn’t a good option for your business. Again, keep it simple. Employees don’t want to read a novel. They just want quick answers so they can carry on with their day. Guiding employees in this way strengthens enterprise AI security while helping your team handle rogue AI in the enterprise.
The Simplified Future: Rogue AI Meets AI Alternatives and Education
In the end, you aren’t competing against just rogue AI at your organization. You are competing against convenience. So, it’s best to approach each policy decision with alternatives that allow for convenience. In doing this, it will keep your corporate data safe for employees to still embrace new approaches for productivity and innovation. AI isn’t going away. It’s here to stay. So, embracing its usage is key to driving your enterprise into the future while ensuring robust AI risk management.
